2573 results about "Network connectivity" patented technology

A video gateway system at a worksite is coupled to multiple cameras on a network, and backs-up video streams generated by the cameras to a backend cloud backup video storage system and a frontend (cache) video storage system. The video gateway system generates an aggregated video asset from a plurality of streams of video from the multiple cameras, and generates metadata and a backup report associated with the video asset. The video asset, metadata, and backup report are stored on the backend cloud backup video storage system in an file system, and are also stored on the frontend (cache) video storage system such that for at least a period of time, the video asset and the associated the metadata and backup report are stored on both the cloud backup video storage system, facilitating quick access and retrieval to the stored video for retrieval for streaming, activity detection, and other uses.

Devices in a wireless communication system perform methods related to a GNSS position fix procedure. A user equipment connected to a network entity via a non-terrestrial network receives a measurement gap configuration and an indication of a remaining-validity-duration-update triggering condition. The UE conducts a GNSS position fix procedure for estimating a UE position during a measurement gap according to the measurement gap configuration. When the GNSS position fix procedure is successfully completed, the UE transmits a remaining GNSS validity duration. When the remaining-validity-duration-update triggering condition is met, the UE transmits an updated remaining GNSS validity duration.

The invention relates to a notebook software vulnerability scanning method based on a security policy. According to the method, firstly, a security policy library of a target notebook is obtained, and the security policy library comprises access control rules, data operation limiting conditions and vulnerability detection reference requirements for different software types; collecting software running data of the target notebook computer, wherein the software running data comprises current running process information, file system operation records, network connection states and software configuration parameters; performing matching analysis on the software operation data and the security policy library to generate a preliminary scanning result; evaluating the risk level of the software vulnerability according to the preliminary scanning result; and finally, based on the risk level and the repair guide terms in the security policy library, generating software vulnerability repair guide information. Therefore, notebook software vulnerabilities can be scanned comprehensively and accurately, and effective repair guidance is provided.

The invention relates to the technical field of network switching, in particular to a heterogeneous network dual-mode self-adaptive switching method and system. According to the method, the multi-dimensional environment sensing data and the initial signal intensity are acquired, the signal intensity is calibrated in a dynamic environment, the dynamic response of the network state to real-time change is realized, and the connection state characteristic and the side network consumption index of the dual-mode network are acquired by combining the calibrated signal intensity. The switching demand can be evaluated on the basis of the data, the switching demand can be judged more accurately through the multi-dimensional evaluation mechanism, the limitation that a traditional method only depends on signal strength is avoided, and the switching demand can be evaluated by generating an optimized directed time sequence graph and a network performance data set. According to the technical scheme, the equipment can make a scientific and reasonable switching decision according to the real-time network state snapshot data and the preset optimization time sequence graph, and the connection requirements of the equipment can be dynamically adapted under the variable network conditions, so that the optimal network experience is kept, and the network connection quality is improved.

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

A system for an automated generation of legal documents based on legal case-related data, including a processor of a legal assistant server (LAS) node configured to host a machine learning (ML) module coupled to a chatbot module and connected to at least one user-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire a user request comprising legal case-related data from the at least one user-entity node; parse the legal case-related data to extract a plurality of key classifying features; acquire legal consultation with the user data from the chatbot module; query a local database to retrieve local historical legal cases′-related data based on the plurality of key classifying features and the legal consultation data; generate at least one classifier vector based on the plurality of the key classifying features, the legal consultation with the user data and the local historical legal cases′-related data; and provide the at least one classifier vector to the ML module configured to generate a legal jurisdiction-based predictive model for producing a set of legal case evaluation parameters for a document generation module configured to generate at least one legal document for the legal case comprising an electronic pleading paper.

The invention discloses a multi-level interconnection network based on real-time flow monitoring and dynamic priority adjustment. A multi-dimensional traffic sensing model is constructed through traffic intensity, queue depth, congestion signals and static priority dynamic indexes. A dynamic urgency value is generated by adopting a configurable weighting strategy, and a three-mode closed-loop optimization mechanism is designed. A layered interconnection structure is adopted, crossbar switches are used in computing clusters, and the computing clusters are connected through a low-diameter routing network. In a cluster gateway, a dynamic arbitration unit monitors the flow intensity in real time, calculates the urgency degree in combination with a queue state and a global congestion signal, and dynamically selects a fixed priority and a weighted polling or polling arbitration strategy. The problem that the resource utilization rate of a traditional static arbitration mechanism is reduced due to task switching is effectively solved, the risk of fairness imbalance in a mixed key data flow scene is effectively solved, and the communication adaptation capacity of a reconfigurable architecture to diversified computing loads is improved.

Optimizing traffic routing operations in a two-box WLAN setup including a gateway device and a WAN adaptor device. The WAN adaptor device receives initial packets of a traffic flow from a client device, and sends the initial packets to the gateway device for slowpath (SP) processing. The gateway device creates fastpath (FP) processing rules for the traffic flow, including traffic modifications resulting from the SP processing, and sends the FP processing rules to the WAN adaptor device. The WAN adaptor device applies the FP processing rules to perform the traffic modifications on subsequent packets of the second traffic flow. The FP processing rules enable the WAN adaptor device to forward the subsequent packets of the traffic flow to the client device directly, without bridging to the gateway device for FP processing.

A secure digital management tool for managing real estate ownership and leases, consisting of: a tamper-proof enclosure containing a secure processing module; a biometric authentication module comprising a fingerprint sensor and an iris scanner, which are operationally coupled with a secure biometric engine to verify a user's physical identity; a document integrity module configured to generate a cryptographic hash of a digital document representing a certificate of ownership or a lease agreement; a smart contract engine configured to compile and execute the logic for legal transactions related to ownership in a Turing-complete virtual machine environment, the logic defining obligations, rights, payment schedules or renewal triggers encoded in the lease or ownership contract; a blockchain interface processing unit operationally connected to the document integrity module and the smart contract engine, wherein the blockchain interface processing unit is configured to anchor cryptographic hashes of the documents and the execution status of smart contracts in a decentralized ledger network; a secure element embedded in the secure processing module and configured to store cryptographic private keys and perform isolated signature and encryption operations without exposing confidential key material to general storage space; a communication subsystem that includes at least one of the following elements: a GSM / 4G module, a Wi-Fi 6 module and a GPS receiver, configured for secure network connectivity and geolocation binding of transactions; a touchscreen interface configured for displaying transaction forms, digital agreements, and interactive contract signing interfaces, the interface also including pen input for capturing digital handwritten signatures; and a secure audit trail subsystem configured to maintain a chronologically ordered, append-only log of all biometric access events, document hash generations, blockchain anchoring events, and smart contract lifecycle transitions, with the audit trail regularly hashed and anchored for forensic integrity in a decentralized blockchain network.

The invention discloses a mobile storage and charging optimization method based on a graph neural network. The method comprises the following steps: collecting operation data of a mobile storage and charging network, and generating node information and edge weights by using the space-time graph neural network; according to the node information and the edge weight, constructing an order insertion sandbox which contains a newly added task association node and keeps network connectivity; executing scheduling optimization in the order insertion sandbox to generate a local scheduling instruction; generating an external resource list in combination with the local scheduling instruction and the boundary node position information, forming a cross-boundary resource candidate set, and completing cross-boundary resource allocation; combining a plurality of order insertion sandboxes meeting a distance threshold condition into a sandbox alliance, and executing joint scheduling to generate an alliance scheduling instruction; and adjusting boundary parameters based on operation record statistics, and applying the boundary parameters to order insertion sandbox generation and scheduling optimization. According to the method, global correlation modeling and dynamic resource scheduling are realized by using the graph neural network, and the cross-regional resource collaboration efficiency and the task completion rate are improved in a complex task environment.

The invention discloses a resource scheduling method and device based on IT asset health assessment, a medium and equipment, and the method comprises the steps: obtaining resource use data, network connection data and abnormal information data corresponding to each node in a distributed system, and carrying out the health degree scoring calculation based on the resource use data, the network connection data and the abnormal information data, obtaining a health degree score corresponding to each node; obtaining the priority of the service adapted to each node, and performing calculation based on the health degree score corresponding to each node and the priority of the adapted service to obtain a comprehensive evaluation value corresponding to each node; and scheduling resources based on the comprehensive evaluation value corresponding to each node. According to the method, the comprehensive evaluation value of multi-modal fusion is calculated, resource scheduling is carried out according to the comprehensive evaluation value, comprehensive and real-time comprehensive evaluation is carried out on the health condition of IT assets, corresponding scheduling processing is carried out according to the comprehensive evaluation condition, and the stability and reliability of the system are remarkably improved.

The invention discloses a new energy power prediction method and system based on a multi-scale state decomposition mechanism, and the method comprises the steps: collecting the multi-source historical data of a wind power station or a photovoltaic station, carrying out the preprocessing of the multi-source historical data, and constructing a training data set; constructing a new energy power prediction network, wherein the new energy power prediction network comprises a knowledge guide layer, a historical sequence encoder, a continuous dynamic system modeling layer and a physical perception decoding network; the knowledge guiding layer is connected with the historical sequence encoder in parallel, and the output of the knowledge guiding layer and the output of the historical sequence encoder are sequentially connected with the continuous dynamic system modeling layer and the physical perception decoding network; training the new energy power prediction network by using the training data set; and deploying the trained new energy power prediction network to a device end, and performing power prediction to obtain a prediction result. According to the method, the stability and the convergence speed of the prediction model in the early training stage and the robustness under the extreme meteorological condition are remarkably improved.

The invention provides a remote management method of a computing card with a built-in network communication unit and the computing card, the computing card is internally provided with the independent network communication unit, and the network communication unit establishes and maintains independent network connection with a remote management platform; the network communication unit collects running state information and network neighbor information of the current computing card, and reports the running state information and the network neighbor information to the remote management platform through the independent network connection; the network communication unit receives a communication control command issued by the host and is used for transmitting TCP / IP data. The computing card can run independently of the host, multiple management of the running state and the network topology can be achieved, the communication capacity is improved, and the hardware integration degree is high.

A method and system for geometrical and topological information analysis for an explainable damage assessment are developed. The system stores pre-disaster and post-disaster point cloud data in computer memory which is connected to a server via a network. The portions of the pre-disaster and post-disaster point cloud data corresponding to the regions of interest are segmented out using geometrical analysis. Features based on topological data analysis techniques for these portions are extracted and stacked as the index reflecting the innate geometrical and topological properties for potential damage assessment. A collection of classifiers are trained to group the damage levels for each region of interest. The damage assessment results identified by the classifiers and a set of explainable items justifying the classification results are reported to a human-readable device.

Aspects of the subject disclosure may include, for example, accessing device usage data that can be generated when end user devices connect with the network; and analyzing the device usage data according to identification information of the deployable cell site, which enables determining or estimating a location of the deployable cell site. In one embodiment, this analysis can be based on device usage reports and network performance data. A performance report and / or location map can be generated for an area associated with the deployable cell site. Other embodiments are disclosed.

The invention relates to the technical field of low-power-consumption data acquisition and transmission, in particular to an NB-IoT network-oriented low-power-consumption data acquisition and transmission system and a medium, and the system comprises a network initialization unit which is used for deploying a data acquisition terminal in a signal attenuation area and defaulting the data acquisition terminal as a working node after power-on; the ferry node election unit is used for acquiring the signal quality score and the residual energy score of the current battery, and calculating a comprehensive score by combining the energy consumption attenuation value; switching the terminal with the highest comprehensive score to a ferry node; the hierarchical data acquisition unit is used for awakening the working node based on a preset awakening strategy, acquiring equipment reading data, sending the equipment reading data to the ferry node, entering a transient monitoring state, and entering a deep dormant state after receiving a receiving confirmation signal of the ferry node; the network interruption data temporary storage and reissuing unit is used for compressing and storing the to-be-transmitted data when the ferry node fails in network connection in the optimal transmission time window; once the network is recovered to be available, resending transmission is performed.

Techniques are provided for distributing performance measurement data to one or more delegating agents. A method includes one or more devices having connectivity to a network sending an identification and configuration request to one or more delegating agents to initiate a performance measurement session in the network, receiving session configuration data associated with the performance measurement session from the one or more delegating agents, and configuring the performance measurement session based on the session configuration data. The method further includes the one or more devices receiving performance measurement data from a reflector in the network during the performance measurement session and distributing the performance measurement data to the one or more delegating agents configured to manage or process the performance measurement data.

The invention discloses a network-on-chip fault-tolerant system based on a fault processing router and a dual fault-tolerant distributed route, and relates to the technical field of network-on-chip. The system comprises a fault processing router and a dual fault-tolerant distributed routing mechanism. The fault processing router comprises a port distribution module, a redirection FIFO module, an error correction module, a crossbar switch module, a crossbar switch bypass module and a detection master control module. The modules cooperate to realize fault isolation and path reconstruction. According to the dual fault-tolerant distributed routing mechanism, fault tolerance is realized through single fault isolation, composite fault collaboration and dynamic routing adjustment, and deadlock is avoided and network connectivity under fault topology is maximized by dynamically relaxing and forbidding a steering rule. The problems of single-point failure and composite fault accumulation caused by permanent faults of transistors of the network-on-chip are solved.

The invention discloses an in-service town gas pipe network remote emergency cut-off valve transformation point selection method, and relates to the technical field of gas pipe network safety control, and the method comprises the steps: constructing a three-dimensional evaluation system comprising a pipe network connectivity index, a valve overflow rate index and an influence user number index, and correcting the importance index weight of the three-dimensional evaluation system; constructing a comprehensive evaluation model based on the three-dimensional evaluation system and the corrected importance index weight, and identifying a plurality of key valves based on the comprehensive evaluation model; based on the leakage consequence severity and rescue timeliness of the key valve, a remote emergency cut-off valve transformation priority evaluation model is constructed, and based on the remote emergency cut-off valve transformation priority evaluation model, the remote emergency cut-off valve transformation point location of the in-service town gas pipe network is determined. The problems of high transformation cost and low gas safety caused by the fact that a transformation point position cannot be reasonably selected by a valve transformation method of an urban gas pipe network which is put into operation are solved.

The invention discloses an automatic grading device for thermal shock cracks of a coating and an application method. Comprising a terahertz wave detection module, a laser ultrasonic excitation and detection module, a high-precision three-dimensional motion control platform, a multi-mode signal synchronous acquisition and processing unit, a crack intelligent grading evaluation unit, an environment simulation and temperature control unit, a protective shell and a human-computer interaction interface. The near-surface dielectric property change of the coating is represented through the terahertz technology, the deep mechanical property evolution is detected through the laser ultrasonic technology, the thermal shock service condition is reproduced in combination with a high-temperature environment simulation unit, and a multi-modal feature fusion algorithm and a physical model and machine learning collaborative inversion model are adopted to obtain the thermal shock resistance of the coating. And automatic quantitative evaluation and severity grading of the depth, density, length and network connectivity of the thermal shock cracks of the thermal barrier coating are realized. The problems that an existing single detection method is insensitive to vertical cracks, poor in high-temperature environment adaptability and low in manual evaluation efficiency are solved.

The invention provides a tunnel fire monitoring and ventilation and smoke exhaust linkage control system. The tunnel fire monitoring and ventilation and smoke exhaust linkage control system comprises a tunnel environment and fire monitoring module, a data fusion processing module, a tunnel ventilation and smoke exhaust linkage control module and a remote monitoring and control management system module which are connected through a communication network. The data fusion processing module is configured with a D-S evidence theory algorithm and is used for receiving multi-source environment data, calculating basic probability distribution of data of each sensor, quantitatively evaluating a fire occurrence probability through a combination rule and generating a fire state judgment result; the tunnel ventilation and smoke exhaust linkage control module is used for receiving the fire state judgment result and determining the target wind speed according to the fire scale; a fuzzy PID control unit and a hysteresis control unit are arranged in the tunnel ventilation and smoke exhaust linkage control module. According to the method, the problem of high false alarm rate of traditional monitoring is solved, the engineering problem that discrete ventilation equipment is difficult to continuously and accurately control is solved, and the disaster prevention and reduction capability of the tunnel is remarkably improved.

Disclosed is a method and apparatus for performing, by a management platform operatively connected to both a video surveillance platform and a positioning platform via network connectivity, at least one among image processing and video analytics on obtained images or video related to a detected asset tag to provide user awareness related to a location or movement of the asset tag in a defined environment.

The invention relates to the technical field of network data security, in particular to a power fgOTN power low-delay secure transmission method. Obtaining a service bearing network topology and link transmission parameters, and constructing a network connection matrix; simulating a flow redistribution process after a fault of a single node, and calculating a topology betweenness centrality index of the substation node; the method comprises the following steps: analyzing payload contents of power business data frames at a fgOTN mapping preceding stage, extracting continuous monitoring features and discrete control features, and calculating a real-time business criticality index of each data frame in combination with a frequency deviation and a voltage fluctuation state of a current network; establishing a two-dimensional decision matrix, and generating a defense strategy according to mapping positions of the topological betweenness centrality index and the criticality index value in the matrix; processing the service data according to the generated defense strategy, and mapping the service data to a fine granularity time slot of the fgOTN; and embedding a security state signaling in the frame overhead, and sending the security state signaling to opposite-end equipment through an optical transmission unit.

The invention discloses a mental health monitoring and nursing robot with body-multi-dimensional intelligent cooperation. The robot comprises a mobile robot platform equipped with a differential driving chassis, a laser SLAM navigation module and the like; a multi-mode sensing network integrating an RGB-D depth camera, a thermal imager and the like processes data in real time through an edge computing unit; an intelligent decision-making engine based on a micro-service architecture covers a patrol recognition module, a vital sign monitoring module, a psychological support Transform dialogue model, a multi-modal emotion recognition module and the like; and the man-machine interaction interface is connected through an end-to-end encrypted 5G network. A medicine compliance management module, an RFID medicine box and a privacy protection scheme of medicine taking action recognition and federal learning and differential privacy are further arranged. The method has the advantages that nursing efficiency is improved by more than 40%, adverse event occurrence rate is reduced by 35%, psychological intervention coverage rate is improved, medicine taking compliance is improved, sublingual Tibetan medicine detection rate is improved to more than 95%, data privacy is safe and controllable, and intelligent upgrading of mental health nursing is promoted.

The invention relates to the technical field of air conditioner refrigeration, and discloses an intelligent energy-saving air conditioner refrigeration system based on the frequency conversion technology and a control method thereof.The intelligent energy-saving air conditioner refrigeration system comprises various sensors used for collecting environment data in real time, and the environment data comprise but not limited to temperature, humidity, illumination and personnel activity information; the control unit is connected with the inverter compressor and the multivariable sensor network and is used for generating a control signal according to the environment data so as to dynamically adjust the operation frequency of the inverter compressor; the control unit comprises a data processing module used for preprocessing environment data collected by the multivariable sensor network; through a multivariable adaptive control algorithm, various environmental factors such as temperature, humidity, illumination and personnel activity information are comprehensively considered, and the operation frequency of the inverter compressor is dynamically adjusted. Compared with a traditional air conditioning system which only depends on a single temperature variable for control, the indoor set temperature can be more precisely maintained, temperature fluctuation is reduced, and the temperature control precision is remarkably improved.

A QR Code Verification Engine provides a multi-layered security framework for generating, validating, and authenticating QR codes while preventing tampering, fraud, and unauthorized access. The system embeds a hidden security layer within the QR code using steganographic encoding or invisible watermarking techniques, ensuring detection of any modifications. The hidden layer is encrypted using asymmetric cryptography, allowing only an authorized verification system to extract and validate it. An AI-powered tamper detection module analyzes QR codes for anomalies, while cryptographic hash verification ensures integrity. The system employs biometric authentication, push notification approvals, and contextual security measures to enhance user verification. Dynamic QR codes with expiration rules prevent replay attacks. Secure offline verification allows authentication without network connectivity. The system integrates with financial platforms, web security tools, and real-time fraud detection mechanisms, ensuring a highly secure and scalable QR code validation framework for transactions, identity verification, and access control applications.

The invention discloses an optimization control method for a power system, and relates to the technical field of power control, and the method comprises the steps: constructing a multi-energy state space, and building a layered optimization architecture based on the multi-energy state space; the decision-making layer generates a multi-energy balance scheduling instruction through a multi-target collaborative optimization algorithm to realize multi-target collaborative optimization of the electric heating gas system; the execution layer comprises a plurality of energy subsystem control modules, and collaborative strategy optimization is carried out through a distributed reinforcement learning algorithm; positioning a disturbance source of topology mutation through a causal reasoning algorithm, and generating a reconstruction instruction; training a control strategy of each energy subsystem by adopting a distributed learning framework, and executing a distributed cooperative control action according to the reconstruction instruction; the network connectivity is judged through the communication state of the energy subsystem, and if the communication is normal, collaborative decision making is carried out through a distributed learning framework; and if the communication is interrupted, switching to an edge node offline autonomous mode.

The invention belongs to the technical field of power distribution network intelligent scheduling, and discloses a power distribution area energy storage adaptive collaborative scheduling method and system.The method comprises the steps that S1, a space-time fluctuation incidence matrix is constructed, cloud cluster data is obtained and preprocessed, and the space-time fluctuation incidence matrix is constructed according to the preprocessed data; s2, developing an edge-cloud cooperative control architecture: edge-cloud cooperative control comprises a cloud side and an edge side, and a bidirectional closed-loop information flow and a control flow are formed through reliable communication network connection; s3, designing a self-adaptive rolling optimization engine: solving the double-layer optimization model in a rolling manner by taking a fixed interval as a period; an LSTM short-term power prediction and correction module is introduced, the fluctuation trend in a period of time in the future is pre-judged, and a photovoltaic fluctuation transmission path caused by cloud layer movement is accurately predicted by constructing a dynamic space-time incidence matrix; an energy storage charging and discharging strategy is optimized through transformer area cluster collaborative scheduling; and the adaptability of the power distribution network to high-proportion renewable energy fluctuation is enhanced.

The invention discloses an Ethernet-based distributed cache coherence protocol, an implementation method, an implementation device and an implementation system. A plurality of computing nodes are connected through a packet switching network. Each computing node comprises a CPU / GPU (Central Processing Unit / Graphics Processing Unit) and a local cache thereof, and is provided with a cache agent. The far-end memory is organized in home nodes, and each home node manages a part of physical address space and is equipped with a directory controller. When the CPU of the computing node accesses a far-end memory address and does not hit in the local cache, the CA of the computing node replaces the far-end memory address and communicates with the DC managing the address through the network so as to maintain the cache consistency of the data among all the nodes. Based on a cache consistency protocol of a directory, the CXL.cache consistency of a plurality of independent computing nodes can be maintained in a low-overhead and high-reliability mode on a high-delay and lossy packet switching network, and broadcast storm caused by a monitoring protocol is avoided.

The invention discloses a park large-screen centralized management and control method and system of an intelligent large-screen management platform, and relates to the technical field of intelligent large-screen management, and the method comprises the steps: building the network connection between a platform and a large screen through the configuration of communication parameters and the input of large-screen equipment identification information, and completing the equipment access authentication through the network connection relation; collecting parameter information and an equipment operation state of the accessed equipment; based on the parameter information of the accessed device, setting a content distribution strategy of a display area, and executing format adaptation and split screen template configuration on the multi-format content; and receiving a voice instruction, completing user identity recognition, and executing alarm grading and display content adjustment according to the collected equipment operation state. According to the method, an access mechanism based on automatic matching of communication parameter configuration and equipment identification information is constructed, so that the access efficiency of heterogeneous large-screen equipment and the automation level of system deployment are effectively improved.